The data_streams.lifecycle.signalling.error_retry_interval setting in Elasticsearch controls the time interval between retry attempts when signalling errors occur during data stream lifecycle management operations.
- Default value: 1h (1 hour)
- Possible values: Time value (e.g., 30m, 2h, 1d)
- Recommendation: The default value is suitable for most use cases, but you may want to adjust it based on your specific requirements and error handling strategy.
This setting determines how long Elasticsearch waits before retrying a failed signalling operation in data stream lifecycle management. Signalling is used to coordinate lifecycle actions across the cluster, and this retry mechanism helps ensure that temporary issues don't permanently disrupt lifecycle management.
This setting is available in Elasticsearch version 7.13.0 and later.
Example
To change the error retry interval to 30 minutes using the cluster settings API:
PUT _cluster/settings
{
"persistent": {
"data_streams.lifecycle.signalling.error_retry_interval": "30m"
}
}
You might want to decrease this interval if you need faster recovery from transient errors, or increase it if you want to reduce the frequency of retry attempts in case of persistent issues.
Common Issues or Misuses
- Setting the interval too low can lead to unnecessary load on the cluster if there are persistent errors.
- Setting the interval too high might delay the resolution of temporary issues, potentially affecting data lifecycle management operations.
Do's and Don'ts
- Do: Monitor your cluster's error logs to understand the frequency and nature of signalling errors.
- Do: Adjust this setting in conjunction with other error handling and monitoring strategies.
- Don't: Set this value extremely low (e.g., seconds) as it may cause excessive retries and cluster load.
- Don't: Ignore persistent signalling errors; investigate and address the root cause.
Frequently Asked Questions
Q: How does this setting affect data stream lifecycle management?
A: It determines how quickly Elasticsearch retries failed signalling operations, which are crucial for coordinating lifecycle actions across the cluster.
Q: Can changing this setting impact cluster performance?
A: Yes, setting a very low retry interval can increase cluster load if there are persistent errors, while a very high interval might delay important lifecycle operations.
Q: Is this setting node-specific or cluster-wide?
A: This is a cluster-wide setting that affects all nodes in the Elasticsearch cluster.
Q: What happens if signalling errors persist beyond retries?
A: Persistent signalling errors may lead to delays or failures in data stream lifecycle management operations. It's important to investigate and resolve underlying issues.
Q: How can I monitor signalling errors in my Elasticsearch cluster?
A: You can monitor signalling errors through Elasticsearch logs, cluster health APIs, and monitoring tools like Kibana or third-party monitoring solutions.
